Layout design on posters is challenging in the sense that it should consider not only graphic relationships but also image compositions, and has attracted continuous research efforts.
Recently, deep-learning-based algorithms [1]}, [2]}, [3]} have been proposed to automatically generate layouts. However, these methods focus more on graphic relationships while ignoring image contents, which is essential for visual-textual posters.
